Title :
Cluster-Based Split-Window Radon Transform Algorithm for Ship Wake Detection
Author :
Na-na, Liu ; Jing-wen, Li ; Yan-feng, Cui
Author_Institution :
Sch. of Electron. & Inf. Eng., BeiHang Univ., Beijing, China
fDate :
March 31 2009-April 2 2009
Abstract :
The purpose of this article is to present a novel algorithm for ship wake detection in synthetic aperture radar (SAR) images. The main originality of our work is that splitting the image with small window before conventional Radon transform to make the illumination has stronger consistency in each window and adopting clustering algorithm to select real wakes form disturbing lines. Experimental result on real SAR image is presented and compared to that obtained using conventional approaches.
Keywords :
Radon transforms; feature extraction; marine radar; oceanographic techniques; pattern clustering; radar detection; radar imaging; ships; synthetic aperture radar; wakes; SAR; cluster-based split-window Radon transform algorithm; linear feature detection; ship wake detection; synthetic aperture radar image; Clustering algorithms; Computer science; Computer vision; Data processing; Gravity; Lighting; Marine vehicles; Radar detection; Synthetic aperture radar; Yield estimation;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.521
